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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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TIME IN SUSPENSE: TEMPORAL REGIMES IN ARTIFICIAL INTELLIGENCE

Authors: Carlos F. De_Angelis;

TIME IN SUSPENSE: TEMPORAL REGIMES IN ARTIFICIAL INTELLIGENCE

Abstract

Artificial intelligence allows us to analyze time from two complementary perspectives: one technical and the other social. From the first perspective, time is a formal structure indispensable for the functioning of systems. Algorithms need to represent sequences, intervals, duration, change, and causality in order to plan, classify, predict, or decide. Time thus appears as a calculable variable translated into mathematical models.From the second perspective, time is a form of organization of collective life. It encompasses work rhythms, institutional timelines, shared memories, expectations, and future projects. From this perspective,artificial intelligence not only uses pre-existing temporalities but also modifies them by accelerating processes, reducing waiting times, and reorganizing everyday decisions.The comparison reveals key differences. For algorithmic logic, the past is a training dataset; for social logic, it is also memory and history. The computational present tends to be compressed through real-time decisions, while the social present requires deliberation, interpretation, and negotiation. The future, for artificial intelligence, is an estimable probability; for society, it is also openness and the possibility of change.Both perspectives agree that time shapes decisions. However, when high-speed technical temporality takes precedence over human and institutional timeframes, tensions arise between efficiency, justice, and autonomy. The central issue is not only what artificial intelligence can do, but what forms of time it produces and governs.

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Keywords

artificial intelligence social time temporality automation prediction.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average